Evidence map›Paper›PMID 35704153›Full record

ArticleAMB Express2022

Characterization of siderophores from Escherichia coli strains through genome mining tools: an antiSMASH study.

Levent Cavas, Ibrahim Kirkiz

Open access · goldAbstract read
In one paragraph

Article in AMB Express, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.2field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Antibiotics (Basel, Switzerland) · 2025
    Article
  3. Review
  4. Article
  5. Article
  6. [ACS infectious diseases · 2024
    Article
  7. Review
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Levent CavasThe Graduate School of Natural and Applied Sciences, Department of Biotechnology, Dokuz Eylül University, Kaynaklar Campus, 35390, İzmir, Türkiye. levent.cavas@deu.edu.tr.ORCID http://orcid.org/0000-0003-2136-6928
Ibrahim KirkizThe Graduate School of Natural and Applied Sciences, Department of Biotechnology, Dokuz Eylül University, Kaynaklar Campus, 35390, İzmir, Türkiye.ORCID http://orcid.org/0000-0002-1602-1901
Dokuz Eylül University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although urinary tract infections (UTIs) affect many people, they are usually a disease observed in women. UTIs happen when exogenous and endogenous bacteria enter the urinary tract and colonize there. Cystitis and pyelonephritis occur when bacteria infect the bladder and the kidneys, respectively. UTIs become much serious if the bacteria causing the infection are antibiotic resistant. Since the pathogenic microorganisms have been adopted to current antibiotics via genetic variations, UTIs have become an even more severe health problem. Therefore, there is a great need for the discovery of novel antibiotics. Genome mining of nonpathogenic and pathogenic Escherichia coli strains for investigating secondary metabolites were conducted by the antiSMASH analysis. When the resulting secondary metabolites were examined, it was found that some of the siderophores are effective in UTIs. In conclusion, since the siderophore production in E. coli is directly related to UTIs, these molecules can be a good target for development of future pharmaceutical approaches and compounds. Siderophores can also be used in industrial studies due to their higher chelating affinity for iron.

Indexed as

BioinformaticsEscherichia coliGenome miningSiderophoresUrinary tract infections

Identifiers

PMID35704153
PMCPMC9200922
OpenAlexW4282964141

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.